Brain Damage and Gene Expression Across Hereditary Spastic Paraplegia Subtypes
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Bibliographic record
Abstract
BACKGROUND: Spinal cord has been considered the main target of damage in hereditary spastic paraplegias (HSPs), but mounting evidence indicates that the brain is also affected. Despite this, little is known about the brain signature of HSPs, in particular regarding stratification for specific genetic subtypes. OBJECTIVE: We aimed to characterize cerebral and cerebellar damage in five HSP subtypes (9 SPG3A, 27 SPG4, 10 SPG7, 9 SPG8, and 29 SPG11) and to uncover the clinical and gene expression correlates. METHODS: We obtained high-resolution brain T1 and diffusion tensor image (DTI) datasets in this cross-sectional case-control study (n = 84). The MRICloud, FreeSurfer, and CERES-SUIT pipelines were employed to assess cerebral gray (GM) and white matter (WM) as well as the cerebellum. RESULTS: Brain abnormalities were found in all but one HSP group (SPG3A), but the patterns were gene-specific: basal ganglia, thalamic, and posterior WM involvement in SPG4; diffuse WM and cerebellar involvement in SPG7; cortical thinning at the motor cortices and pallidal atrophy in SPG8; and widespread GM, WM, and deep cerebellar nuclei damage in SPG11. Abnormal regions in SPG4 and SPG8 matched those with higher SPAST and WASHC5 expression, whereas in SPG7 and SPG11 this concordance was only noticed in the cerebellum. CONCLUSIONS: Brain damage is a conspicuous feature of HSPs (even for pure subtypes), but the pattern of abnormalities is genotype-specific. Correlation between brain structural damage and gene expression maps is different for autosomal dominant and recessive HSPs, pointing to distinct pathophysiological mechanisms underlying brain damage in these subgroups of the disease. © 2021 International Parkinson and Movement Disorder Society.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it